8991555 1935 Hilde Weerts 3481 Supervised Classification 8317 sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklearn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,clf=sklearn.svm.classes.SVC)(1) 6927110 categorical_features [] 7644 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 7644 handle_unknown "ignore" 7644 n_values "auto" 7644 sparse true 7644 threshold 0.0 7645 copy true 7646 with_mean false 7646 with_std true 7646 C 0.4784301353425586 7650 cache_size 200 7650 class_weight null 7650 coef0 0.1968190084970649 7650 decision_function_shape "ovr" 7650 degree 3 7650 gamma 0.00035564910488405363 7650 kernel "rbf" 7650 max_iter -1 7650 probability false 7650 random_state 1 7650 shrinking false 7650 tol 6.127397202936418e-05 7650 verbose false 7650 axis 0 8316 categorical_features [] 8316 copy true 8316 fill_empty 0 8316 missing_values "NaN" 8316 strategy "mean" 8316 strategy_nominal "most_frequent" 8316 verbose 0 8316 memory null 8317 openml-python Sklearn_0.19.1. study_98 300 isolet https://www.openml.org/data/download/52405/phpB0xrNj -1 18898071 description https://api.openml.org/data/download/18898071/description.xml -1 18898072 predictions https://api.openml.org/data/download/18898072/predictions.arff area_under_roc_curve 0.9721896493448081 [0.990733,0.955798,0.990933,0.951733,0.951333,0.983366,0.972266,0.991667,0.993,0.992666,0.984266,0.994133,0.958804,0.925466,0.981467,0.927666,0.996133,0.9964,0.969667,0.922533,0.981066,0.929866,0.996733,0.986533,0.993267,0.959466] average_cost 0 f_measure 0.9464592315912252 [0.968801,0.86385,0.973597,0.912752,0.903654,0.947541,0.946667,0.991597,0.985025,0.976898,0.966777,0.97377,0.896104,0.891986,0.976351,0.870152,0.983498,0.990033,0.960818,0.897527,0.966555,0.883959,0.959872,0.983165,0.991625,0.945205] kappa 0.9443786464984634 kb_relative_information_score 7374.98691642699 mean_absolute_error 0.00411400834640541 mean_prior_absolute_error 0.07396449117237175 number_of_instances 7797 [300,300,300,300,300,298,300,300,300,300,300,300,299,300,300,300,300,300,300,300,300,300,300,300,300,300] precision 0.9474711460797436 [0.954693,0.814159,0.964052,0.918919,0.900662,0.926282,0.946667,1,0.983389,0.96732,0.963576,0.958065,0.870662,0.934307,0.989726,0.880546,0.973856,0.986755,0.982578,0.954887,0.969799,0.905594,0.925697,0.993197,0.996633,0.971831] predictive_accuracy 0.9465178914967295 prior_entropy 4.700438289429255 recall 0.9465178914967295 [0.983333,0.92,0.983333,0.906667,0.906667,0.969799,0.946667,0.983333,0.986667,0.986667,0.97,0.99,0.923077,0.853333,0.963333,0.86,0.993333,0.993333,0.94,0.846667,0.963333,0.863333,0.996667,0.973333,0.986667,0.92] relative_absolute_error 0.05562139725693309 root_mean_prior_squared_error 0.19230768465256318 root_mean_squared_error 0.06414053590675253 root_relative_squared_error 0.3335307999918642 total_cost 0 area_under_roc_curve 0.9713333333333333 [0.981333,0.948,0.998667,0.980667,0.948,0.999333,0.948667,0.983333,1,0.999333,0.965333,0.999333,0.948667,0.948667,0.983333,0.915333,1,1,0.999333,0.898,0.981333,0.946667,0.998667,0.966667,0.983333,0.932667] area_under_roc_curve 0.9726666666666666 [0.981333,0.963333,1,0.949333,0.979333,0.998667,0.982667,0.983333,0.982667,0.998667,0.965333,0.998667,0.965333,0.965333,0.966667,0.88,0.999333,0.999333,0.966667,0.916,0.966667,0.931333,0.999333,0.983333,1,0.966667] area_under_roc_curve 0.9700000000000002 [0.998667,0.947333,0.982667,0.914,0.947333,0.981333,0.966667,0.983333,0.966,0.983333,0.964667,0.983333,0.981333,0.932667,0.999333,0.93,1,0.982667,0.949333,0.914,0.999333,0.981333,0.998667,0.983333,0.999333,0.95] area_under_roc_curve 0.9740000000000002 [0.999333,0.995333,0.982667,0.982667,0.983333,0.998667,0.997333,0.983333,1,0.982667,0.998667,0.983333,0.945333,0.898,0.999333,0.898,0.982667,1,0.983333,0.9,0.982667,0.866,0.999333,0.982667,1,0.999333] area_under_roc_curve 0.9653333333333337 [0.998667,0.925333,0.982,0.981333,0.948,0.946667,0.998,1,0.982667,0.983333,1,0.983333,0.996,0.883333,0.999333,0.966,0.999333,0.999333,0.915333,0.916667,0.982667,0.831333,0.981333,0.983333,0.983333,0.932] area_under_roc_curve 0.9806666666666668 [1,0.98,1,0.949333,0.966,0.982667,0.982667,1,1,0.999333,1,0.999333,0.947333,0.932,0.983333,0.898,1,1,1,0.949333,1,0.947333,0.998667,0.982667,1,0.999333] area_under_roc_curve 0.9680000000000001 [0.982667,0.962667,0.999333,0.948,0.864,0.982,0.998667,0.983333,0.999333,0.999333,0.982667,0.998,0.913333,0.914,0.966667,0.914,0.982667,0.983333,0.966667,0.949333,0.965333,0.966,0.996667,1,0.983333,0.966667] area_under_roc_curve 0.9739724076546505 [0.999332,0.929328,0.983333,0.931998,0.94733,0.998665,0.949332,1,1,0.999332,1,0.998665,0.960184,0.848665,0.966667,0.997997,1,1,0.966667,0.915999,0.999332,0.949332,0.998665,1,1,0.981998] area_under_roc_curve 0.9712968402314196 [1,0.943992,0.982666,0.930663,0.947997,0.981425,0.965999,1,1,0.983333,0.999332,0.999332,0.965332,0.965999,0.983333,0.92866,0.997997,0.999332,0.983333,0.883333,0.95,0.931331,0.997997,1,1,0.932666] area_under_roc_curve 0.9746355140186916 [0.965999,0.962661,0.997997,0.949332,0.981998,0.963517,0.932666,1,0.999332,0.997997,0.966667,0.997997,0.965332,0.965999,0.966667,0.948665,0.999332,1,0.965999,0.982666,0.983333,0.947997,0.997997,0.983333,0.983333,0.933333] average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 f_measure 0.9445317415884686 [0.935484,0.9,0.967742,0.920635,0.9,0.983607,0.915254,0.983051,1,0.983607,0.933333,0.983607,0.915254,0.915254,0.983051,0.877193,1,1,0.983607,0.842105,0.935484,0.870968,0.967742,0.965517,0.983051,0.912281] f_measure 0.9473300357926128 [0.935484,0.888889,1,0.931034,0.892308,0.967742,0.966667,0.983051,0.966667,0.967742,0.933333,0.967742,0.933333,0.933333,0.965517,0.793103,0.983607,0.983607,0.965517,0.892857,0.965517,0.881356,0.983607,0.983051,1,0.965517] f_measure 0.9422901588184022 [0.967742,0.885246,0.966667,0.847458,0.885246,0.935484,0.965517,0.983051,0.949153,0.983051,0.918033,0.983051,0.935484,0.912281,0.983607,0.852459,1,0.966667,0.931034,0.847458,0.983607,0.935484,0.967742,0.983051,0.983607,0.947368] f_measure 0.9493143835698502 [0.983607,0.895522,0.966667,0.966667,0.983051,0.967742,0.9375,0.983051,1,0.966667,0.967742,0.983051,0.84375,0.842105,0.983607,0.842105,0.966667,1,0.983051,0.888889,0.966667,0.830189,0.983607,0.966667,1,0.983607] f_measure 0.9329869576191387 [0.967742,0.764706,0.95082,0.935484,0.9,0.870968,0.952381,1,0.966667,0.983051,1,0.983051,0.909091,0.867925,0.983607,0.949153,0.983607,0.983607,0.877193,0.909091,0.966667,0.754717,0.935484,0.983051,0.983051,0.896552] f_measure 0.962624336674511 [1,0.90625,1,0.931034,0.949153,0.966667,0.966667,1,1,0.983607,1,0.983607,0.885246,0.896552,0.983051,0.842105,1,1,1,0.931034,1,0.885246,0.967742,0.966667,1,0.983607] f_measure 0.9381933328255614 [0.966667,0.875,0.983607,0.9,0.785714,0.95082,0.967742,0.983051,0.983607,0.983607,0.966667,0.952381,0.833333,0.847458,0.965517,0.847458,0.966667,0.983051,0.965517,0.931034,0.933333,0.949153,0.923077,1,0.983051,0.965517] f_measure 0.9494804624545882 [0.983607,0.83871,0.983051,0.896552,0.885246,0.967742,0.931034,1,1,0.983607,1,0.967742,0.84375,0.792453,0.965517,0.952381,1,1,0.965517,0.892857,0.983607,0.931034,0.967742,1,1,0.95082] f_measure 0.9450472999433794 [1,0.818182,0.966667,0.866667,0.9,0.949153,0.949153,1,1,0.983051,0.983607,0.983607,0.933333,0.949153,0.983051,0.825397,0.952381,0.983607,0.983051,0.867925,0.947368,0.881356,0.952381,1,1,0.912281] f_measure 0.9512999176537987 [0.949153,0.875,0.952381,0.931034,0.95082,0.915254,0.912281,1,0.983607,0.952381,0.965517,0.952381,0.933333,0.949153,0.965517,0.915254,0.983607,1,0.949153,0.966667,0.983051,0.9,0.952381,0.983051,0.983051,0.928571] kappa 0.9426666666666667 kappa 0.9453333333333332 kappa 0.94 kappa 0.948 kappa 0.9306666666666666 kappa 0.9613333333333334 kappa 0.9359999999999999 kappa 0.9479336973398731 kappa 0.9425930718199284 kappa 0.9492682960269133 kb_relative_information_score 736.4847466945296 kb_relative_information_score 738.5095778015775 kb_relative_information_score 734.4608927616237 kb_relative_information_score 740.5324477288402 kb_relative_information_score 727.3744673504021 kb_relative_information_score 750.6497357190805 kb_relative_information_score 731.4211946263213 kb_relative_information_score 739.5325243030977 kb_relative_information_score 735.4818338717328 kb_relative_information_score 740.5394955690854 mean_absolute_error 0.0042406311637080895 mean_absolute_error 0.004043392504930968 mean_absolute_error 0.00443786982248521 mean_absolute_error 0.0038461538461538477 mean_absolute_error 0.0051282051282051325 mean_absolute_error 0.002859960552268244 mean_absolute_error 0.004733727810650891 mean_absolute_error 0.003851091142490374 mean_absolute_error 0.004246074849412465 mean_absolute_error 0.003752345215759851 mean_prior_absolute_error 0.07396449704142057 mean_prior_absolute_error 0.07396449704142057 mean_prior_absolute_error 0.07396449704142057 mean_prior_absolute_error 0.07396449704142057 mean_prior_absolute_error 0.07396449704142057 mean_prior_absolute_error 0.07396449704142057 mean_prior_absolute_error 0.07396449704142057 mean_prior_absolute_error 0.07396448587535052 mean_prior_absolute_error 0.07396447325283656 mean_prior_absolute_error 0.07396447325283656 number_of_instances 780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30] number_of_instances 780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30] number_of_instances 780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30] number_of_instances 780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30] number_of_instances 780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30] number_of_instances 780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30] number_of_instances 780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30] number_of_instances 779 [30,30,30,30,30,30,30,30,30,30,30,30,29,30,30,30,30,30,30,30,30,30,30,30,30,30] number_of_instances 779 [30,30,30,30,30,29,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30] number_of_instances 779 [30,30,30,30,30,29,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30] precision 0.9455853915427053 [0.90625,0.9,0.9375,0.878788,0.9,0.967742,0.931034,1,1,0.967742,0.933333,0.967742,0.931034,0.931034,1,0.925926,1,1,0.967742,0.888889,0.90625,0.84375,0.9375,1,1,0.962963] precision 0.9490834572396885 [0.90625,0.848485,1,0.964286,0.828571,0.9375,0.966667,1,0.966667,0.9375,0.933333,0.9375,0.933333,0.933333,1,0.821429,0.967742,0.967742,1,0.961538,1,0.896552,0.967742,1,1,1] precision 0.9435032291226673 [0.9375,0.870968,0.966667,0.862069,0.870968,0.90625,1,1,0.965517,1,0.903226,1,0.90625,0.962963,0.967742,0.83871,1,0.966667,0.964286,0.862069,0.967742,0.90625,0.9375,1,0.967742,1] precision 0.9525980253034539 [0.967742,0.810811,0.966667,0.966667,1,0.9375,0.882353,1,1,0.966667,0.9375,1,0.794118,0.888889,0.967742,0.888889,0.966667,1,1,1,0.966667,0.956522,0.967742,0.966667,1,0.967742] precision 0.937769522798488 [0.9375,0.684211,0.935484,0.90625,0.9,0.84375,0.909091,1,0.966667,1,1,1,0.833333,1,0.967742,0.965517,0.967742,0.967742,0.925926,1,0.966667,0.869565,0.90625,1,1,0.928571] precision 0.9633519790078547 [1,0.852941,1,0.964286,0.965517,0.966667,0.966667,1,1,0.967742,1,0.967742,0.870968,0.928571,1,0.888889,1,1,1,0.964286,1,0.870968,0.9375,0.966667,1,0.967742] precision 0.93972054826684 [0.966667,0.823529,0.967742,0.9,0.846154,0.935484,0.9375,1,0.967742,0.967742,0.966667,0.909091,0.833333,0.862069,1,0.862069,0.966667,1,1,0.964286,0.933333,0.965517,0.857143,1,1,1] precision 0.9520362289256311 [0.967742,0.8125,1,0.928571,0.870968,0.9375,0.964286,1,1,0.967742,1,0.9375,0.771429,0.913043,1,0.909091,1,1,1,0.961538,0.967742,0.964286,0.9375,1,1,0.935484] precision 0.9480895175068275 [1,0.75,0.966667,0.866667,0.9,0.933333,0.965517,1,1,1,0.967742,0.967742,0.933333,0.965517,1,0.787879,0.909091,0.967742,1,1,1,0.896552,0.909091,1,1,0.962963] precision 0.9533644033713371 [0.965517,0.823529,0.909091,0.964286,0.935484,0.9,0.962963,1,0.967742,0.909091,1,0.909091,0.933333,0.965517,1,0.931034,0.967742,1,0.965517,0.966667,1,0.9,0.909091,1,1,1] predictive_accuracy 0.9448717948717948 predictive_accuracy 0.9474358974358974 predictive_accuracy 0.9423076923076923 predictive_accuracy 0.95 predictive_accuracy 0.9333333333333332 predictive_accuracy 0.9628205128205128 predictive_accuracy 0.9384615384615383 predictive_accuracy 0.9499358151476252 predictive_accuracy 0.944801026957638 predictive_accuracy 0.951219512195122 prior_entropy 4.700438289429255 prior_entropy 4.700438289429255 prior_entropy 4.700438289429255 prior_entropy 4.700438289429255 prior_entropy 4.700438289429255 prior_entropy 4.700438289429255 prior_entropy 4.700438289429255 prior_entropy 4.700438289429255 prior_entropy 4.700438289429255 prior_entropy 4.700438289429255 recall 0.9448717948717948 [0.966667,0.9,1,0.966667,0.9,1,0.9,0.966667,1,1,0.933333,1,0.9,0.9,0.966667,0.833333,1,1,1,0.8,0.966667,0.9,1,0.933333,0.966667,0.866667] recall 0.9474358974358974 [0.966667,0.933333,1,0.9,0.966667,1,0.966667,0.966667,0.966667,1,0.933333,1,0.933333,0.933333,0.933333,0.766667,1,1,0.933333,0.833333,0.933333,0.866667,1,0.966667,1,0.933333] recall 0.9423076923076923 [1,0.9,0.966667,0.833333,0.9,0.966667,0.933333,0.966667,0.933333,0.966667,0.933333,0.966667,0.966667,0.866667,1,0.866667,1,0.966667,0.9,0.833333,1,0.966667,1,0.966667,1,0.9] recall 0.95 [1,1,0.966667,0.966667,0.966667,1,1,0.966667,1,0.966667,1,0.966667,0.9,0.8,1,0.8,0.966667,1,0.966667,0.8,0.966667,0.733333,1,0.966667,1,1] recall 0.9333333333333333 [1,0.866667,0.966667,0.966667,0.9,0.9,1,1,0.966667,0.966667,1,0.966667,1,0.766667,1,0.933333,1,1,0.833333,0.833333,0.966667,0.666667,0.966667,0.966667,0.966667,0.866667] recall 0.9628205128205128 [1,0.966667,1,0.9,0.933333,0.966667,0.966667,1,1,1,1,1,0.9,0.866667,0.966667,0.8,1,1,1,0.9,1,0.9,1,0.966667,1,1] recall 0.9384615384615385 [0.966667,0.933333,1,0.9,0.733333,0.966667,1,0.966667,1,1,0.966667,1,0.833333,0.833333,0.933333,0.833333,0.966667,0.966667,0.933333,0.9,0.933333,0.933333,1,1,0.966667,0.933333] recall 0.9499358151476252 [1,0.866667,0.966667,0.866667,0.9,1,0.9,1,1,1,1,1,0.931034,0.7,0.933333,1,1,1,0.933333,0.833333,1,0.9,1,1,1,0.966667] recall 0.944801026957638 [1,0.9,0.966667,0.866667,0.9,0.965517,0.933333,1,1,0.966667,1,1,0.933333,0.933333,0.966667,0.866667,1,1,0.966667,0.766667,0.9,0.866667,1,1,1,0.866667] recall 0.9512195121951219 [0.933333,0.933333,1,0.9,0.966667,0.931034,0.866667,1,1,1,0.933333,1,0.933333,0.933333,0.933333,0.9,1,1,0.933333,0.966667,0.966667,0.9,1,0.966667,0.966667,0.866667] relative_absolute_error 0.05733333333333302 relative_absolute_error 0.05466666666666636 relative_absolute_error 0.05999999999999967 relative_absolute_error 0.0519999999999997 relative_absolute_error 0.06933333333333297 relative_absolute_error 0.038666666666666426 relative_absolute_error 0.06399999999999967 relative_absolute_error 0.05206676010674188 relative_absolute_error 0.05740695042737462 relative_absolute_error 0.05073172363349384 root_mean_prior_squared_error 0.19230769991209876 root_mean_prior_squared_error 0.19230769991209876 root_mean_prior_squared_error 0.19230769991209876 root_mean_prior_squared_error 0.19230769991209876 root_mean_prior_squared_error 0.19230769991209876 root_mean_prior_squared_error 0.19230769991209876 root_mean_prior_squared_error 0.19230769991209876 root_mean_prior_squared_error 0.19230767088031558 root_mean_prior_squared_error 0.19230763806177284 root_mean_prior_squared_error 0.19230763806177284 root_mean_squared_error 0.06512012871384769 root_mean_squared_error 0.06358767573147306 root_mean_squared_error 0.06661733875264915 root_mean_squared_error 0.06201736729460424 root_mean_squared_error 0.07161148740394332 root_mean_squared_error 0.0534785990118313 root_mean_squared_error 0.06880209161537817 root_mean_squared_error 0.06205716028380911 root_mean_squared_error 0.06516191256717735 root_mean_squared_error 0.0612563891831689 root_relative_squared_error 0.3386246559218025 root_relative_squared_error 0.33065590072856227 root_relative_squared_error 0.346410147815709 root_relative_squared_error 0.32249029717973615 root_relative_squared_error 0.37237971977552625 root_relative_squared_error 0.2780887038650852 root_relative_squared_error 0.35777086225266425 root_relative_squared_error 0.32269726943149835 root_relative_squared_error 0.3388420409294721 root_relative_squared_error 0.31853331360396714 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 usercpu_time_millis 86733.73792301572 usercpu_time_millis 94996.20807298925 usercpu_time_millis 85748.79390200658 usercpu_time_millis 80428.14114299836 usercpu_time_millis 76476.11799598963 usercpu_time_millis 82162.31894301018 usercpu_time_millis 77272.94128799986 usercpu_time_millis 76095.0257400109 usercpu_time_millis 76738.09294500097 usercpu_time_millis 75758.47393700678 usercpu_time_millis_testing 3584.707159010577 usercpu_time_millis_testing 3690.4898719949415 usercpu_time_millis_testing 3675.1872500026366 usercpu_time_millis_testing 3675.985338006285 usercpu_time_millis_testing 3505.2907219942426 usercpu_time_millis_testing 3652.3203670076327 usercpu_time_millis_testing 3604.6681600128068 usercpu_time_millis_testing 3865.097018002416 usercpu_time_millis_testing 3552.178270998411 usercpu_time_millis_testing 3527.249970007688 usercpu_time_millis_training 83149.03076400515 usercpu_time_millis_training 91305.7182009943 usercpu_time_millis_training 82073.60665200395 usercpu_time_millis_training 76752.15580499207 usercpu_time_millis_training 72970.82727399538 usercpu_time_millis_training 78509.99857600254 usercpu_time_millis_training 73668.27312798705 usercpu_time_millis_training 72229.92872200848 usercpu_time_millis_training 73185.91467400256 usercpu_time_millis_training 72231.2239669991